On Reducing Network Usage with Genetic Improvement

被引:0
作者
Callan, James [1 ]
Langdon, William B. [1 ]
Petke, Justyna [1 ]
机构
[1] UCL, Dept Comp Sci, Gower St, London, England
来源
PROCEEDINGS OF THE 2024 IEEE/ACM INTERNATIONAL WORKSHOP ON GENETIC IMPROVEMENT, GI@ICSE 2024 | 2024年
基金
英国工程与自然科学研究理事会;
关键词
genetic programming; genetic improvement; SBSE; HTTP; GIDroid; Robolectric; SOFTWARE;
D O I
10.1145/3643692.3648262
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Mobile applications can be very network-intensive. Mobile phone users are often on limited data plans, while network infrastructure has limited capacity. There's little work on optimizing network usage of mobile applications. The most popular approach has been prefetching and caching assets. However, past work has shown that developers can improve the network usage of Android applications by making changes to Java source code. We built upon this insight and investigated the effectiveness of automated, heuristic application of software patches, a technique known as Genetic Improvement (GI), to improve network usage. Genetic improvement has already shown effective at reducing the execution time and memory usage of Android applications. We thus adapt our existing GIDroid framework with a new mutation operator and develop a new profiler to identify network-intensive methods to target. Unfortunately, our approach is unable to find improvements. We conjecture this is due to the fact source code changes affecting network might be rare in the large patch search space. We thus advocate use of more intelligent search strategies in future work.
引用
收藏
页码:23 / 30
页数:8
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